<html>
<head>
<title>
Netlab Reference Manual demtrain
</title>
</head>
<body>
<H1> demtrain
</H1>
<h2>
Purpose
</h2>
Demonstrate training of MLP network.

<p><h2>
Synopsis
</h2>
<PRE>
demtrain</PRE>


<p><h2>
Description
</h2>
<CODE>demtrain</CODE> brings up a simple GUI to show the training of
an MLP network on classification and regression problems.  The user
should load in a dataset (which should be in Netlab format: see 
<CODE>datread</CODE>), select the output activation function, the
 number of cycles and hidden units and then
train the network. The scaled conjugate gradient algorithm is used.
A graph shows the evolution of the error: the value is shown 
<CODE>max(ceil(iterations / 50), 5)</CODE> cycles.

<p>Once the network is trained, it is saved to the file <CODE>mlptrain.net</CODE>.
The results can then be viewed as a confusion matrix (for classification
problems) or a plot of output versus target (for regression problems).

<p><h2>
See Also
</h2>
<CODE><a href="confmat.htm">confmat</a></CODE>, <CODE><a href="datread.htm">datread</a></CODE>, <CODE><a href="mlp.htm">mlp</a></CODE>, <CODE><a href="netopt.htm">netopt</a></CODE>, <CODE><a href="scg.htm">scg</a></CODE><hr>
<b>Pages:</b>
<a href="index.htm">Index</a>
<hr>
<p>Copyright (c) Ian T Nabney (1996-9)


</body>
</html>